[Hiring] AI/ML Engineer @AM.Dirac

Role Description

We are looking for a full-time AI/ML Engineer to join the core team at AM.Dirac. This is an opportunity to build intelligent systems that power next-generation trading strategies, from idea generation to execution. You’ll work at the intersection of state-of-the-art ML (including LLMs and agentic systems), portfolio optimization, and real-time data pipelines. Your work will directly support live strategies in production and lay the foundation for autonomous investment agents.

Key Responsibilities

• Alpha Generation: Design and refine predictive ML models trained on intraday financial data and alternative datasets to surface trade signals.
• Data Infrastructure & Experimentation: Work with large-scale time series, macroeconomic, and unstructured datasets. Build pipelines, clean data, and rapidly iterate on hypotheses.
• Agentic Systems Development: Help architect and implement systems using LLMs to automate alpha research, backtesting, and live trading tasks.
• Portfolio Optimization: Contribute to the design of intelligent portfolio construction methods that integrate learned signals and risk constraints.
• Tooling & Research Ops: Develop internal experimentation frameworks in Python/Jupyter and build reproducible research workflows across the team.
• Collaboration: Work closely with quant researchers, founders, and systems engineers to scale model impact from prototype to production.

Qualifications

• Education: BS in Computer Science, Machine Learning, or related field (MS/PhD preferred). Exceptional candidates without a degree but with strong evidence of technical ability will be considered.
• Python & Jupyter Expertise: Demonstrated fluency with Python, NumPy, pandas, scikit-learn, and Jupyter for ML development and research.
• ML Proficiency: Experience with supervised learning, time series modeling, and neural networks. Bonus points for hands-on use of LLMs or reinforcement learning frameworks.
• Experimentation Mindset: Ability to rapidly test, measure, and iterate on model-based systems in noisy or nonstationary environments.
• Curiosity for Markets: While no prior finance experience is required, you should be motivated to learn how markets behave and how ML can exploit inefficiencies.

Preferred

• LLM & Agentic Workflows: Familiarity with prompting strategies, RAG, fine-tuning, or frameworks like LangChain, Transformers, or OpenAI APIs. Experience working with messy and unstructured data as inputs to modeling tasks.
• Open Source Contributions or Research: Active GitHub, blog posts, or published work showing initiative and originality in applied ML.
• Quantitative Finance: Experience building backend infrastructure for algorithmic trading and conducting research to originate market signals and trading strategies highly preferred.

Benefits

• High Impact, Early Team Role: Shape the design and function of our AI-native investment platform from the ground up.
• Research-to-Production: See your work go from notebook to production in live trading strategies.
• Fast Iteration, Deep Focus: No bureaucracy, no endless meetings. Just focused execution with elite peers.
• Compensation: Competitive base salary + performance-linked bonus + benefits.
• Culture: Intellectually honest, independently driven, and curious about the edge of AI and finance.

Application Process

Interested candidates should submit:

• Resume/CV highlighting your technical background and ML experience
• Optional: Links to open-source projects, GitHub repos, or writing samples
• Brief note (if you'd like) on why you're excited about joining an AI-native trading firm

AM.Dirac is an equal opportunity employer. We value diverse perspectives and are committed to building a team that reflects a wide range of backgrounds and experiences.